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1. Expression profile of HERVs and inflammatory mediators detected in nasal mucosa as a predictive biomarker of COVID-19 severity

Author

Petrone, V, Fanelli, M, Giudice, M, Toschi, N, Conti, A, Maracchioni, C, Iannetta, M, Resta, C, Cipriani, C, Miele, Mt, Amati, F, Andreoni, M, Sarmati, L, Rogliani, P, Novelli, G, Garaci, E, Rasi, G, Sinibaldi-Vallebona, P, Minutolo, A, Matteucci, C, Balestrieri, E, and Grelli, S

Subjects
Microbiology (medical), Microbiology, Settore MED/07
Abstract

IntroductionOur research group and others demonstrated the implication of the human endogenous retroviruses (HERVs) in SARS-CoV-2 infection and their association with disease progression, suggesting HERVs as contributing factors in COVID-19 immunopathology. To identify early predictive biomarkers of the COVID-19 severity, we analyzed the expression of HERVs and inflammatory mediators in SARS-CoV-2-positive and -negative nasopharyngeal/oropharyngeal swabs with respect to biochemical parameters and clinical outcome.MethodsResiduals of swab samples (20 SARS-CoV-2-negative and 43 SARS-CoV-2-positive) were collected during the first wave of the pandemic and expression levels of HERVs and inflammatory mediators were analyzed by qRT-Real time PCR.ResultsThe results obtained show that infection with SARS-CoV-2 resulted in a general increase in the expression of HERVs and mediators of the immune response. In particular, SARS-CoV-2 infection is associated with increased expression of HERV-K and HERV-W, IL-1β, IL-6, IL-17, TNF-α, MCP-1, INF-γ, TLR-3, and TLR-7, while lower levels of IL-10, IFN-α, IFN-β, and TLR-4 were found in individuals who underwent hospitalization. Moreover, higher expression of HERV-W, IL-1β, IL-6, IFN-α, and IFN-β reflected the respiratory outcome of patients during hospitalization. Interestingly, a machine learning model was able to classify hospitalized vs not hospitalized patients with good accuracy based on the expression levels of HERV-K, HERV-W, IL-6, TNF-a, TLR-3, TLR-7, and the N gene of SARS-CoV-2. These latest biomarkers also correlated with parameters of coagulation and inflammation.DiscussionOverall, the present results suggest HERVs as contributing elements in COVID-19 and early genomic biomarkers to predict COVID-19 severity and disease outcome.

Published
2023
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3. Time-resolved connectome of the five-factor model of personality

Author

Passamonti L 1, 2, Riccelli R 3, Indovina I 3, 4 Duggento A 5, Terracciano A 6, Toschi N 5, Duggento, A. [0000-0001-6030-5269], Terracciano, A. [0000-0001-5799-8885], Toschi, N. [0000-0003-1929-5833], Apollo - University of Cambridge Repository, Duggento, A [0000-0001-6030-5269], Terracciano, A [0000-0001-5799-8885], and Toschi, N [0000-0003-1929-5833]

Subjects
Adult, Male, 141, Time Factors, 639/705/531, media_common.quotation_subject, lcsh:Medicine, 631/378/2649/1725, Models, Biological, 050105 experimental psychology, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Surveys and Questionnaires, Connectome, Image Processing, Computer-Assisted, Personality, Humans, 0501 psychology and cognitive sciences, Generalizability theory, Big Five personality traits, lcsh:Science, Default mode network, media_common, Multidisciplinary, Settore FIS/07, 05 social sciences, Statistics, lcsh:R, article, Conscientiousness, Cognition, Magnetic Resonance Imaging, Trait, 59/36, Female, lcsh:Q, Nerve Net, Psychology, 030217 neurology & neurosurgery, Cognitive psychology
Abstract

The human brain is characterized by highly dynamic patterns of functional connectivity. However, it is unknown whether this time-variant ‘connectome’ is related to the individual differences in the behavioural and cognitive traits described in the five-factor model of personality. To answer this question, inter-network time-variant connectivity was computed in n = 818 healthy people via a dynamical conditional correlation model. Next, network dynamicity was quantified throughout an ad-hoc measure (T-index) and the generalizability of the multi-variate associations between personality traits and network dynamicity was assessed using a train/test split approach. Conscientiousness, reflecting enhanced cognitive and emotional control, was the sole trait linked to stationary connectivity across several circuits such as the default mode and prefronto-parietal network. The stationarity in the ‘communication’ across large-scale networks offers a mechanistic description of the capacity of conscientious people to ‘protect’ non-immediate goals against interference over-time. This study informs future research aiming at developing more realistic models of the brain dynamics mediating personality differences.

Published
2019
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4. Renal Function, Adherence and Quality of Life Improvement After Conversion From Immediate to Prolonged-Release Tacrolimus in Liver Transplantation: Prospective Ten-Year Follow-Up Study

Author

Toti, L, Manzia, Tm, Blasi, F, Lenci, I, Baiocchi, L, Toschi, N, and Tisone, G

Subjects
Transplantation, immunosuppression, liver transplantation, quality of life, adherence, Tacrolimus, Settore MED/18
Abstract

Immunosuppression non-adherence is a major cause of graft failure after liver transplantation. The aim of this study was to evaluate practice surrounding conversion from immediate-release to prolonged-release Tacrolimus formulation and to assess patient adherence and quality of life (QoL). One hundred and seven adult liver transplant recipients, receiving immediate-release Tacrolimus for a minimum of 6 months, were converted to prolonged-release formulation, based on a dose ratio of one (1:1). The median follow-up was 120 [IQR, 120–123] months. Tacrolimus dosage and blood level, liver and renal function, lipid and glucose profiles were recorded. In addition, questionnaires were submitted to evaluate adherence and QoL following conversion. No rejection was recorded. The median serum Tacrolimus blood level decreased over 1 month (5.80, [IQR, 2.0–10.8] vs. 3.8 [IQR, 1.4–8.7]; p < 0.0005). Significant improvement in renal function was noted (median GFR was 81.7 [IQR, 43.4–128.6] vs. 73.9 [IQR, 27.1–130.2]; p = 0.0002). At the end of the follow-up, conversion resulted in an overall decrease in non-adherence of 53.3% (p = 0.0001) and an improvement in QoL was reported by 76.2% of patients. Thus, 1:1 conversion from immediate to prolonged-release Tacrolimus is safe, feasible and efficient, avoiding under-therapeutic and toxic peak concentrations, improving renal function, adherence to immunosuppression and overall patient QoL.

Published
2022

5. Aptamarker prediction of brain amyloid-β status in cognitively normal individuals at risk for Alzheimer’s disease

Author

Penner, G, Lecocq, S, Chopin, A, Vedoya, X, Lista, S, Vergallo, A, Cavedo, E, Lejeune, F, Dubois, B, Hampel, H, Bakardjian, H, Benali, H, Bertin, H, Bonheur, J, Boukadida, L, Boukerrou, N, Chiesa, Pa, Colliot, O, Dubois, M, Epelbaum, S, Gagliardi, G, Genthon, R, Habert, M, Houot, M, Kas, A, Lamari, F, Levy, M, Metzinger, C, Mochel, F, Nyasse, F, Poisson, C, Potier, M, Revillon, M, Santos, A, Andrade, Ks, Sole, M, Surtee, M, de Schotten, Mt, Younsi, N, Afshar, M, Aguilar, Lf, Akman-Anderson, L, Aremas, J, Avila, J, Babiloni, C, Baldacci, F, Batrla, R, Benda, N, Black, Kl, Bokde, Alw, Bonuccelli, U, Broich, K, Cacciola, F, Caraci, F, Caruso, G, Castrillo, J, Ceravolo, R, Corbo, M, Corvol, J, Cuello, Ac, Cummings, Jl, Depypere, H, Duggento, A, Emanuele, E, Escott-Price, V, Federoff, H, Ferretti, Mt, Fiandaca, M, Frank, Ra, Garaci, F, Geerts, H, Giacobini, E, Giorgi, Fs, Goetzl, Ej, Graziani, M, Haberkamp, M, Hanisch, B, Herholz, K, Hernandez, F, Imbimbo, Bp, Kapogiannis, D, Karran, E, Kiddle, Sj, Kim, Sh, Koronyo, Y, Koronyo-Hamaoui, M, Langevin, T, Lehericy, S, Lemercier, P, Llavero, F, Lorenceau, J, Lucia, A, Mango, D, Mapstone, M, Neri, C, Nistico, R, O'Bryant, Se, Palermo, G, Perry, G, Ritchie, C, Rossi, S, Saidi, A, Santarnecchi, E, Schneider, Ls, Sporns, O, Toschi, N, Valenzuela, Pl, Vellas, B, Verdooner, Sr, Villain, N, Giudici, Kv, Watling, M, Welikovitch, La, Woodcock, J, Younesi, E, Zugaza, Jl, Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Gasset, Maria

Subjects
Male, Aging, Amyloid β, MESH: SELEX Aptamer Technique, [SDV]Life Sciences [q-bio], Oligonucleotides, Artificial Gene Amplification and Extension, Disease, Neurodegenerative, Alzheimer's Disease, Pathology and Laboratory Medicine, Biochemistry, Polymerase Chain Reaction, Diagnostic Radiology, Negative selection, Medical Conditions, Mathematical and Statistical Techniques, 0302 clinical medicine, MESH: Aged, 80 and over, MESH: Early Diagnosis, 80 and over, Medicine and Health Sciences, Biomarker discovery, Tomography, Aged, 80 and over, MESH: Aged, screening and diagnosis, 0303 health sciences, Multidisciplinary, Nucleotides, Mathematical Models, Radiology and Imaging, SELEX Aptamer Technique, Settore MED/37 - Neuroradiologia, Neurodegenerative Diseases, MESH: Case-Control Studies, MESH: Amyloid beta-Peptides, Detection, Neurology, Neurological, Medicine, Biomedical Imaging, Female, Biotechnology, 4.2 Evaluation of markers and technologies, Research Article, Amyloid, General Science & Technology, Imaging Techniques, Science, Aptamer, Neuroimaging, and over, Computational biology, Biology, Research and Analysis Methods, 03 medical and health sciences, Clinical Research, Diagnostic Medicine, Alzheimer Disease, Mental Health and Psychiatry, Acquired Cognitive Impairment, Humans, Risk factor, Molecular Biology Techniques, Molecular Biology, Aged, 030304 developmental biology, Amyloid beta-Peptides, MESH: Humans, Prevention, Neurosciences, Alzheimer Precision Medicine Initiative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Biology and Life Sciences, Omics, MESH: Male, Brain Disorders, 4.1 Discovery and preclinical testing of markers and technologies, Early Diagnosis, Case-Control Studies, MESH: Biomarkers, Dementia, INSIGHT-preAD study group, MESH: Female, Biomarkers, Positron Emission Tomography, 030217 neurology & neurosurgery, MESH: Alzheimer Disease, Neuroscience
Abstract

International audience; The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer's disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices.

Published
2021
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7. Age and sex impact plasma NFL and t-Tau trajectories in individuals with subjective memory complaints: a 3-year follow-up study

Author

Baldacci, F., Lista, S., Manca, M. L., Chiesa, P. A., Cavedo, E., Lemercier, P., Zetterberg, H., Blennow, K., Habert, M. -O., Potier, M. C., Dubois, B., Vergallo, A., Hampel, H., Bakardjian, H., Benali, H., Bertin, H., Bonheur, J., Boukadida, L., Boukerrou, N., Chiesa, P., Colliot, O., Dubois, M., Epelbaum, S., Gagliardi, G., Genthon, R., Houot, M., Kas, A., Lamari, F., Levy, M., Metzinger, C., Mochel, F., Nyasse, F., Poisson, C., Potier, M. -C., Revillon, M., Santos, A., Andrade, K. S., Sole, M., Surtee, M., de Schotten, M. T., Younsi, N., Afshar, M., Aguilar, L. F., Akman-Anderson, L., Arenas, J., Avila, J., Babiloni, C., Batrla, R., Benda, N., Black, K. L., Bokde, A. L. W., Bonuccelli, U., Broich, K., Cacciola, F., Caraci, F., Caruso, G., Castrillo, J., Ceravolo, R., Corbo, M., Corvol, J. -C., Claudio, A., Cummings, J. L., Depypere, H., Duggento, A., Emanuele, E., Escott-Price, V., Federoff, H., Ferretti, M. T., Fiandaca, M., Frank, R. A., Garaci, F., Geerts, H., Giacobini, E., Giorgi, F. S., Goetzl, E. J., Graziani, M., Haberkamp, M., Hanisch, B., Herholz, K., Hernandez, F., Imbimbo, B. P., Kapogiannis, D., Karran, E., Kiddle, S. J., Kim, S. H., Koronyo, Y., Koronyo-Hamaoui, M., Langevin, T., Lehericy, S., Llavero, F., Lorenceau, J., Lucia, A., Mango, D., Mapstone, M., Neri, C., Nistico, R., O'Bryant, S. E., Palermo, G., Perry, G., Ritchie, C., Rossi, S., Saidi, A., Santarnecchi, E., Schneider, L. S., Sporns, O., Toschi, N., Valenzuela, P. L., Vellas, B., Verdooner, S. R., Villain, N., Virecoulon Giudici, K., Watling, M., Welikovitch, L. A., Woodcock, J., Younesi, E., Zugaza, J. L., Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), University of Pisa - Università di Pisa, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Sahlgrenska Academy at University of Gothenburg [Göteborg], University College of London [London] (UCL), UK Dementia Research Institute (UK DRI), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de médecine nucléaire [CHU Pitié-Salpétrière], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, BIOMARKER, 0301 basic medicine, Oncology, Aging, Neurology, [SDV]Life Sciences [q-bio], Disease, Neurodegenerative, Alzheimer's Disease, Medical and Health Sciences, lcsh:RC346-429, MESH: Cognitive Dysfunction, Alzheimer’s disease, Biomarkers, Mild cognitive impairment, Neurofilament light chain, Subjective memory complainers, Tau, 0302 clinical medicine, Neurofilament Proteins, Medicine and Health Sciences, BRAIN, MESH: Neurofilament Proteins, RISK, Settore FIS/07, NEURODEGENERATION, Cognition, ASSOCIATION, MESH: Follow-Up Studies, Alzheimer's disease, MESH: Amyloid beta-Peptides, MESH: tau Proteins, ALZHEIMERS-DISEASE, POSITIVITY, Neurological, Cohort, Biomarker (medicine), Female, medicine.medical_specialty, Cognitive Neuroscience, tau Proteins, Subjective, Affect (psychology), VALIDATION, lcsh:RC321-571, subjective memory complainers, mild cognitive impairment, biomarkers, s disease, 03 medical and health sciences, memory complainers, Clinical Research, Alzheimer Disease, Internal medicine, NEUROFILAMENT LIGHT-CHAIN, Acquired Cognitive Impairment, medicine, Humans, Cognitive Dysfunction, Vitamin B12, Allele, Alzheimer&#8217, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, lcsh:Neurology. Diseases of the nervous system, Amyloid beta-Peptides, MESH: Humans, business.industry, Research, Prevention, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer Precision Medicine Initiative, COGNITIVE IMPAIRMENT, MESH: Male, Brain Disorders, 030104 developmental biology, MESH: Biomarkers, Dementia, Neurology (clinical), business, INSIGHT-preAD study group, MESH: Female, MESH: Alzheimer Disease, 030217 neurology & neurosurgery, Follow-Up Studies
Abstract

Background Plasma neurofilament light (NFL) and total Tau (t-Tau) proteins are candidate biomarkers for early stages of Alzheimer’s disease (AD). The impact of biological factors on their plasma concentrations in individuals with subjective memory complaints (SMC) has been poorly explored. We longitudinally investigate the effect of sex, age, APOE ε4 allele, comorbidities, brain amyloid-β (Aβ) burden, and cognitive scores on plasma NFL and t-Tau concentrations in cognitively healthy individuals with SMC, a condition associated with AD development. Methods Three hundred sixteen and 79 individuals, respectively, have baseline and three-time point assessments (at baseline, 1-year, and 3-year follow-up) of the two biomarkers. Plasma biomarkers were measured with an ultrasensitive assay in a mono-center cohort (INSIGHT-preAD study). Results We show an effect of age on plasma NFL, with women having a higher increase of plasma t-Tau concentrations compared to men, over time. The APOE ε4 allele does not affect the biomarker concentrations while plasma vitamin B12 deficiency is associated with higher plasma t-Tau concentrations. Both biomarkers are correlated and increase over time. Baseline NFL is related to the rate of Aβ deposition at 2-year follow-up in the left-posterior cingulate and the inferior parietal gyri. Baseline plasma NFL and the rate of change of plasma t-Tau are inversely associated with cognitive score. Conclusion We find that plasma NFL and t-Tau longitudinal trajectories are affected by age and female sex, respectively, in SMC individuals. Exploring the influence of biological variables on AD biomarkers is crucial for their clinical validation in blood.

Published
2020
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8. β-Secretase1 biological markers for Alzheimer’s disease: state-of-art of validation and qualification

Author

Hampel, H., Lista, S., Vanmechelen, E., Zetterberg, H., Giorgi, F. S., Galgani, A., Blennow, K., Caraci, F., Das, B., Yan, R., Vergallo, A., Aguilar, L. F., Akman-Anderson, L., Arenas, J., Avila, J., Babiloni, C., Baldacci, F., Batrla, R., Benda, N., Black, K. L., Bokde, A. L. W., Bonuccelli, U., Broich, K., Cacciola, F., Caruso, G., Castrillo, J., Cavedo, E., Ceravolo, R., Chiesa, P. A., Corbo, M., Corvol, J. -C., Cuello, A. C., Cummings, J. L., Depypere, H., Dubois, B., Duggento, A., Emanuele, E., Escott-Price, V., Federoff, H., Ferretti, M. T., Fiandaca, M., Frank, R. A., Garaci, F., Geerts, H., Giacobini, E., Goetzl, E. J., Graziani, M., Haberkamp, M., Habert, M. -O., Hanisch, B., Herholz, K., Hernandez, F., Imbimbo, B. P., Kapogiannis, D., Karran, E., Kiddle, S. J., Kim, S. H., Koronyo, Y., Koronyo-Hamaoui, M., Langevin, T., Lehericy, S., Lemercier, P., Llavero, F., Lorenceau, J., Lucia, A., Mango, D., Mapstone, M., Neri, C., Nistico, R., O'Bryant, S. E., Palermo, G., Perry, G., Ritchie, C., Rossi, S., Saidi, A., Santarnecchi, E., Schneider, L. S., Sporns, O., Toschi, N., Valenzuela, P. L., Vellas, B., Verdooner, S. R., Villain, N., Virecoulon Giudici, K., Watling, M., Welikovitch, L. A., Woodcock, J., Younesi, E., and Zugaza, J. L.

Subjects
BIOMARKER, 0301 basic medicine, Aging, Neurology, Fluid biomarkers, Axonal damage, context of use, Review, Alzheimer’s disease, Amyloid-β pathway, BACE1, clinical trials, fluid biomarkers, neurodegeneration, Disease, Neurodegenerative, Bioinformatics, Medical and Health Sciences, lcsh:RC346-429, Clinical trials, 0302 clinical medicine, PP-BETA, Medicine and Health Sciences, Aspartic Acid Endopeptidases, Context of use, Neurodegeneration, Amyloid Precursor Protein Secretases, Amyloid beta-Peptides, Biomarkers, Humans, Alzheimer Disease, RISK, screening and diagnosis, CORRELATE, Settore FIS/07, AMYLOID-PRECURSOR PROTEIN, Alzheimer's disease, Detection, Neurological, State of art, Biomarker (medicine), EXPRESSION, medicine.medical_specialty, Cognitive Neuroscience, lcsh:RC321-571, 03 medical and health sciences, CEREBROSPINAL-FLUID, Clinical Research, BETA-SECRETASE BACE1, mental disorders, Acquired Cognitive Impairment, medicine, Adverse effect, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, lcsh:Neurology. Diseases of the nervous system, Mechanism (biology), business.industry, Prevention, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Amyloid-beta pathway, medicine.disease, Brain Disorders, 4.1 Discovery and preclinical testing of markers and technologies, Clinical trial, Good Health and Well Being, 030104 developmental biology, Dementia, Alzheimer’s Precision Medicine Initiative, Neurology (clinical), TAU, business, 030217 neurology & neurosurgery, GENERATION
Abstract

β-Secretase1 (BACE1) protein concentrations and rates of enzyme activity, analyzed in human bodily fluids, are promising candidate biological markers for guidance in clinical trials investigating BACE1 inhibitors to halt or delay the dysregulation of the amyloid-β pathway in Alzheimer’s disease (AD). A robust body of evidence demonstrates an association between cerebrospinal fluid/blood BACE1 biomarkers and core pathophysiological mechanisms of AD, such as brain protein misfolding and aggregration, neurodegeneration, and synaptic dysfunction.In pharmacological trials, BACE1 candidate biomarkers may be applied to a wide set of contexts of use (CoU), including proof of mechanism, dose-finding, response and toxicity dose estimation. For clinical CoU, BACE1 biomarkers show good performance for prognosis and disease prediction.The roadmap toward validation and qualification of BACE1 biomarkers requires standardized pre-analytical and analytical protocols to reduce inter-site variance that may have contributed to inconsistent results.BACE1 biomarker-drug co-development programs, including biomarker-guided outcomes and endpoints, may support the identification of sub-populations with a higher probability to benefit from BACE1 inhibitors with a reduced risk of adverse effects, in line with the evolving precision medicine paradigm.

Published
2020
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9. Breast Osteoblast-like Cells: A Reliable Early Marker for Bone Metastases From Breast Cancer

Author

Scimeca, M, Antonacci, C, Toschi, N, Giannini, E, Bonfiglio, R, Buonomo, Co, Pistolese, Ca, Tarantino, U, Bonanno, E, and Buonomo, Oc

Subjects
Bone metastasis, Bone morphogenetic proteins (BMPs), Epithelial to mesenchymal transition (EMT), PTX3, RANKL, 0301 basic medicine, Cancer Research, Epithelial-Mesenchymal Transition, Bone Neoplasms, Breast Neoplasms, Settore MED/08 - Anatomia Patologica, Calcitriol receptor, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Biomarkers, Tumor, Tumor Microenvironment, Carcinoma, medicine, Humans, Breast, skin and connective tissue diseases, Retrospective Studies, Osteoblasts, biology, business.industry, RANK Ligand, Mesenchymal stem cell, Osteoblast, medicine.disease, Serum Amyloid P-Component, C-Reactive Protein, 030104 developmental biology, medicine.anatomical_structure, Oncology, 030220 oncology & carcinogenesis, Bone Morphogenetic Proteins, Cancer research, biology.protein, Receptors, Calcitriol, Immunohistochemistry, Female, business
Abstract

Background The development of bone metastasis from breast cancer results from a functional interaction between tumor cells and osteoclasts or osteoblasts. The main aim of this study was therefore to test the hypothesis that the appearance of breast osteoblast-like cells (BOLCs) in primary mammary lesions is a precursor (and hence an early predictor) of the formation of breast cancer metastases to bone. Patients and Methods In this study, we collected 64 breast infiltrating carcinomas, 50 breast benignant lesions, and 10 biopsies of bone metastasis selected from patients with infiltrated carcinoma. Immunohistochemical, western blot, and ultrastructural analysis allowed us to investigate the presence of BOLCs in breast cancer lesions and metastatic sites. Results We established the presence of a high amount of breast cancer cells that underwent mesenchymal transformation in infiltrating carcinomas. In addition, our results demonstrated that the microenvironment of breast cancer is very similar to the microenvironment of bone. We noted a significantly higher expression of BMP-2/4 and PTX3 in breast-infiltrating carcinomas compared with benign lesions. Moreover, we also identified numerous BOLCs positive to RANKL and Vitamin D receptor. Thanks to ultrastructural analysis, we also revealed the presence of BOLCs at the metastatic site. Conclusions The identification of breast cancer cells with high affinity for a bone environment opens new perspectives on prevention and therapy of bone metastases from breast.

Published
2018
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10. Differential default mode network trajectories in asymptomatic individuals at risk for Alzheimer's disease

Author

Chiesa P. A., Cavedo E., Vergallo A., Lista S., Potier M. -C., Habert M. -O., Dubois B., Thiebaut de Schotten M., Hampel H., Audrain C., Auffret A., Bakardjian H., Baldacci F., Batrancourt B., Benakki I., Benali H., Bertin H., Bertrand A., Boukadida L., Cacciamani F., Causse V., Cherif Touil S., Colliot O., Dalla Barba G., Depaulis M., Dos Santos A., Dubois M., Epelbaum S., Fontaine B., Francisque H., Gagliardi G., Genin A., Genthon R., Glasman P., Gombert F., Habert M. O., Hewa H., Houot M., Jungalee N., Kas A., Kilani M., La Corte V., Le Roy F., Lehericy S., Letondor C., Levy M., Lowrey M., Ly J., Makiese O., Masetti I., Mendes A., Metzinger C., Michon A., Mochel F., Nait Arab R., Nyasse F., Perrin C., Poirier F., Poisson C., Potier M. C., Ratovohery S., Revillon M., Rojkova K., Santos-Andrade K., Schindler R., Servera M. C., Seux L., Simon V., Skovronsky D., Uspenskaya O., Vlaincu M., Aguilar L. F., Babiloni C., Benda N., Black K. L., Bokde A. L. W., Bonuccelli U., Broich K., Cacciola F., Castrillo J., Ceravolo R., Corvol J. -C., Claudio Cuello A., Cummings J. L., Depypere H., Duggento A., Durrleman S., Escott-Price V., Federoff H., Teresa Ferretti M., Fiandaca M., Frank R. A., Garaci F., Geerts H., George N., Giorgi F. S., Graziani M., Haberkamp M., Herholz K., Karran E., Kim S. H., Koronyo Y., Koronyo-Hamaoui M., Lamari F., Langevin T., Lorenceau J., Mango D., Mapstone M., Neri C., Nistico R., O'Bryant S. E., Palermo G., Perry G., Ritchie C., Rossi S., Saidi A., Santarnecchi E., Schneider L. S., Sporns O., Toschi N., Verdooner S. R., Villain N., Welikovitch L. A., Woodcock J., Younesi E., Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neuroradiologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Treat SVD, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), sans affiliation, Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB), Service de neurologie 1 [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Service de médecine nucléaire [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre des Maladies Cognitives et Comportementales [Paris], Fraunhofer Center for Assistive Information and Communication Solutions [Porto] (Fraunhofer AICOS), Fraunhofer (Fraunhofer-Gesellschaft), Ariana Pharmaceuticals, McGill University = Université McGill [Montréal, Canada], Universidad Autonoma de Madrid (UAM), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], University of Pisa - Università di Pisa, Federal Institute of Drugs and Medical Devices [Bonn], Discipline of Psychiatry [Dublin], School of Medicine [Dublin], Trinity College Dublin-Trinity College Dublin, Universita degli Studi di Messina, University of Catania [Italy], University of Cambridge [UK] (CAM), Lou Ruvo Center for Brain Health [Las Vegas], Cleveland Clinic, Università degli Studi di Roma Tor Vergata [Roma], University of Pavia, Cardiff University, Universität Zürich [Zürich] = University of Zurich (UZH), University of California [Irvine] (UCI), University of California, Siemens Healthineers, Digital Services, Digital Technology and Innovation, In Silico Biosciences (ISB), Abdus Salam International Centre for Theoretical Physics [Trieste] (ICTP), University of California [San Francisco] (UCSF), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), University of Manchester [Manchester], National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Abbvie Inc. [North Chicago], Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University of Britsh Columbia [Vancouver], Cedars-Sinai Medical Center, Functional Neuromodulation, CIBER de Enfermedades Raras (CIBERER), Institut de la Vision, Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), European Brain Research Institute [Rome, Italy] (EBRI), Adaptation Biologique et Vieillissement = Biological Adaptation and Ageing (B2A), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institute for Aging and Alzheimer’s Disease Research [Fort Worth] (IAADR), University of North Texas Health Science Center [Fort Worth], University of Auckland [Auckland], University of Edinburgh, Università degli Studi di Siena = University of Siena (UNISI), Harvard Medical School [Boston] (HMS), Keck School of Medicine [Los Angeles], University of Southern California (USC), Indiana State University, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), NeuroVision Imaging, Fondation pour la Recherche sur Alzheimer, Center for Drug Evaluation and Research (CDER), European Society for Translational Medicine (EUSTM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service d'Explorations Fonctionnelles Neurologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de médecine nucléaire [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), Fraunhofer AICOS [Porto], McGill University, Sapienza University [Rome], University of Zürich [Zürich] (UZH), Università degli Studi di Roma 'La Sapienza' [Rome], CHU Pitié-Salpêtrière [APHP], Service de neuro-radiologie [CHU Pitié-Salpêtrière], Università degli Studi di Siena (UNISI), Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Service de Médecine nucléaire [CHU Pitié-Salpétrière], Universidad Autónoma de Madrid (UAM), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Sans affiliation, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), Università degli Studi di Messina = University of Messina (UniMe), Università degli Studi di Pavia = University of Pavia (UNIPV), University of California [Irvine] (UC Irvine), University of California (UC), University of California [San Francisco] (UC San Francisco), University of British Columbia [Vancouver], Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Chiesa, P. A., Cavedo, E., Vergallo, A., Lista, S., Potier, M. -C., Habert, M. -O., Dubois, B., Thiebaut de Schotten, M., Hampel, H., Audrain, C., Auffret, A., Bakardjian, H., Baldacci, F., Batrancourt, B., Benakki, I., Benali, H., Bertin, H., Bertrand, A., Boukadida, L., Cacciamani, F., Causse, V., Cherif Touil, S., Colliot, O., Dalla Barba, G., Depaulis, M., Dos Santos, A., Dubois, M., Epelbaum, S., Fontaine, B., Francisque, H., Gagliardi, G., Genin, A., Genthon, R., Glasman, P., Gombert, F., Habert, M. O., Hewa, H., Houot, M., Jungalee, N., Kas, A., Kilani, M., La Corte, V., Le Roy, F., Lehericy, S., Letondor, C., Levy, M., Lowrey, M., Ly, J., Makiese, O., Masetti, I., Mendes, A., Metzinger, C., Michon, A., Mochel, F., Nait Arab, R., Nyasse, F., Perrin, C., Poirier, F., Poisson, C., Potier, M. C., Ratovohery, S., Revillon, M., Rojkova, K., Santos-Andrade, K., Schindler, R., Servera, M. C., Seux, L., Simon, V., Skovronsky, D., Uspenskaya, O., Vlaincu, M., Aguilar, L. F., Babiloni, C., Benda, N., Black, K. L., Bokde, A. L. W., Bonuccelli, U., Broich, K., Cacciola, F., Castrillo, J., Ceravolo, R., Corvol, J. -C., Claudio Cuello, A., Cummings, J. L., Depypere, H., Duggento, A., Durrleman, S., Escott-Price, V., Federoff, H., Teresa Ferretti, M., Fiandaca, M., Frank, R. A., Garaci, F., Geerts, H., George, N., Giorgi, F. S., Graziani, M., Haberkamp, M., Herholz, K., Karran, E., Kim, S. H., Koronyo, Y., Koronyo-Hamaoui, M., Lamari, F., Langevin, T., Lorenceau, J., Mango, D., Mapstone, M., Neri, C., Nistico, R., O'Bryant, S. E., Palermo, G., Perry, G., Ritchie, C., Rossi, S., Saidi, A., Santarnecchi, E., Schneider, L. S., Sporns, O., Toschi, N., Verdooner, S. R., Villain, N., Welikovitch, L. A., Woodcock, J., Younesi, E., and Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Apolipoprotein E, Epidemiology, Brain activity and meditation, Precuneus, Disease, Neuropsychological Tests, Hippocampus, Cohort Studies, [SCCO]Cognitive science, 0302 clinical medicine, Medicine, Longitudinal Studies, Default mode network, ComputingMilieux_MISCELLANEOUS, Brain Mapping, Subjective memory complaints, Brain functional dynamic, Health Policy, Precision medicine, fMRI, Settore BIO/14, Brain, Brain functional dynamics, Alzheimer's disease, Magnetic Resonance Imaging, Temporal Lobe, Frontal Lobe, Psychiatry and Mental health, medicine.anatomical_structure, Cohort, Biomarker (medicine), Female, Amyloid, 03 medical and health sciences, Cellular and Molecular Neuroscience, Apolipoproteins E, Developmental Neuroscience, Alzheimer Disease, Humans, Aged, Resting state fMRI, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, 030104 developmental biology, Neurology (clinical), Geriatrics and Gerontology, business, Neuroscience, 030217 neurology & neurosurgery
Abstract

Introduction The longitudinal trajectories of functional brain dynamics and the impact of genetic risk factors in individuals at risk for Alzheimer's disease are poorly understood. Methods In a large-scale monocentric cohort of 224 amyloid stratified individuals at risk for Alzheimer's disease, default mode network (DMN) resting state functional connectivity (FC) was investigated between two serial time points across 2 years. Results Widespread DMN FC changes were shown in frontal and posterior areas, as well as in the right hippocampus. There were no cross-sectional differences, however, apolipoprotein E e4 (APOE e4) carriers demonstrated slower increase in FC in frontal lobes. There was no impact of individual brain amyloid load status. Discussion For the first time, we demonstrated that the pleiotropic biological effect of the APOE e4 allele impacts the dynamic trajectory of the DMN during aging. Dynamic functional biomarkers may become useful surrogate outcomes for the development of preclinical targeted therapeutic interventions.

Published
2019
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11. Blink Rate Behavioral Pattern Changes in Patients Affected by Acute Stroke: A Cross-Sectional Study

Author

Damulin, Ferrazzano G, Toschi N, Spallone A, Li Voti P, Tinelli E, Nardella A, and Belvisi D

Subjects
medicine.medical_specialty, Physical medicine and rehabilitation, Cross-sectional study, business.industry, medicine, Behavioral pattern, Montreal Cognitive Assessment, In patient, General Medicine, medicine.disease, business, Stroke, Acute stroke
Published
2019
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12. Association of cerebrospinal fluid α-synuclein with total and phospho-tau181 protein concentrations and brain amyloid load in cognitively normal subjective memory complainers stratified by Alzheimer's disease biomarkers

Author

Vergallo, A, Bun, R, Toschi, N, Baldacci, F, Zetterberg, H, Blennow, K, Cavedo, E, Lamari, F, Habert, M, Dubois, B, Floris, R, Garaci, F, Lista, S, Hampel, H, Audrain, C, Auffret, A, Bakardjian, H, Batrancourt, B, Benakki, I, Benali, H, Bertin, H, Bertrand, A, Boukadida, L, Cacciamani, F, Causse, V, Cherif Touil, S, Chiesa, Pa, Colliot, O, Dalla Barba, G, Depaulis, M, Dos Santos, A, Dubois, M, Epelbaum, S, Fontaine, B, Francisque, H, Gagliardi, G, Genin, A, Genthon, R, Glasman, P, Gombert, F, Habert, Mo, Hewa, H, Houot, M, Jungalee, N, Kas, A, Kilani, M, La Corte, V, Le Roy, F, Lehericy, S, Letondor, C, Levy, M, Lowrey, M, Ly, J, Makiese, O, Masetti, I, Mendes, A, Metzinger, C, Michon, A, Mochel, F, Nait Arab, R, Nyasse, F, Perrin, C, Poirier, F, Poisson, C, Potier, Mc, Ratovohery, S, Revillon, M, Rojkova, K, Santos-Andrade, K, Schindler, R, Servera, Mc, Seux, L, Simon, V, Skovronsky, D, Thiebaut, M, Uspenskaya, O, Vlaincu, M, Aguilar, Lf, Babiloni, C, Benda, N, Black, Kl, Bokde, Alw, Bonuccelli, U, Broich, K, Bun, Rs, Cacciola, F, Castrillo, J, Ceravolo, R, Coman, Cm, Corvol, Jc, Cuello, Ac, Cummings, Jl, Depypere, H, Duggento, A, Durrleman, S, Escott-Price, V, Federoff, H, Ferretti, Mt, Fiandaca, M, Frank, Ra, George, N, Giorgi, Fs, Graziani, M, Haberkamp, M, Herholz, K, Karran, E, Kim, Sh, Koronyo, Y, Koronyo-Hamaoui, M, Langevin, T, Lehéricy, S, Lorenceau, J, Mapstone, M, Neri, C, Nisticò, R, Nyasse-Messene, F, O'Bryant, Se, Perry, G, Ritchie, C, Rossi, S, Santarnecchi, E, Schneider, Ls, Sporns, O, Verdooner, Sr, Villain, N, Welikovitch, L, Woodcock, J, Younesi, E, Vergallo, A., Bun, R. -S., Toschi, N., Baldacci, F., Zetterberg, H., Blennow, K., Cavedo, E., Lamari, F., Habert, M. -O., Dubois, B., Floris, R., Garaci, F., Lista, S., Hampel, H., Audrain, C., Auffret, A., Bakardjian, H., Batrancourt, B., Benakki, I., Benali, H., Bertin, H., Bertrand, A., Boukadida, L., Cacciamani, F., Causse, V., Cherif Touil, S., Chiesa, P. A., Colliot, O., Dalla Barba, G., Depaulis, M., Dos Santos, A., Dubois, M., Epelbaum, S., Fontaine, B., Francisque, H., Gagliardi, G., Genin, A., Genthon, R., Glasman, P., Gombert, F., Habert, M. O., Hewa, H., Houot, M., Jungalee, N., Kas, A., Kilani, M., La Corte, V., Le Roy, F., Lehericy, S., Letondor, C., Levy, M., Lowrey, M., Ly, J., Makiese, O., Masetti, I., Mendes, A., Metzinger, C., Michon, A., Mochel, F., Nait Arab, R., Nyasse, F., Perrin, C., Poirier, F., Poisson, C., Potier, M. C., Ratovohery, S., Revillon, M., Rojkova, K., Santos-Andrade, K., Schindler, R., Servera, M. C., Seux, L., Simon, V., Skovronsky, D., Thiebaut, M., Uspenskaya, O., Vlaincu, M., Aguilar, L. F., Babiloni, C., Benda, N., Black, K. L., Bokde, A. L. W., Bonuccelli, U., Broich, K., Bun, R. S., Cacciola, F., Castrillo, J., Ceravolo, R., Coman, C. M., Corvol, J. C., Cuello, A. C., Cummings, J. L., Depypere, H., Duggento, A., Durrleman, S., Escott-Price, V., Federoff, H., Ferretti, M. T., Fiandaca, M., Frank, R. A., George, N., Giorgi, F. S., Graziani, M., Haberkamp, M., Herholz, K., Karran, E., Kim, S. H., Koronyo, Y., Koronyo-Hamaoui, M., Langevin, T., Lorenceau, J., Mapstone, M., Neri, C., Nistico, R., Nyasse-Messene, F., O'Bryant, S. E., Perry, G., Ritchie, C., Rossi, S., Santarnecchi, E., Schneider, L. S., Sporns, O., Verdooner, S. R., Villain, N., Welikovitch, L., Woodcock, J., and Younesi, E.

Subjects
0301 basic medicine, Epidemiology, Alzheimer's disease, Amyloid PET, Cerebrospinal fluid, Monocentric, Preclinical, Subjective memory complainers, SUVR, Synergistic, Tau protein, α-Synuclein, chemistry.chemical_compound, 0302 clinical medicine, biology, Health Policy, Settore FIS/07, Settore BIO/14, Pathophysiology, Psychiatry and Mental health, medicine.symptom, medicine.medical_specialty, Amyloid, Asymptomatic, 03 medical and health sciences, Cellular and Molecular Neuroscience, Developmental Neuroscience, Neurology (clinical), Geriatrics and Gerontology, Psychiatry and Mental Health, Internal medicine, mental disorders, medicine, Dementia, Alpha-synuclein, business.industry, Alzheimer's disease biomarkers, medicine.disease, 030104 developmental biology, Endocrinology, nervous system, chemistry, Subjective memory complainer, biology.protein, business, 030217 neurology & neurosurgery
Abstract

Introduction Several neurodegenerative brain proteinopathies, including Alzheimer's disease (AD), are associated with cerebral deposition of insoluble aggregates of α-synuclein. Previous studies reported a trend toward increased cerebrospinal fluid (CSF) α-synuclein (α-syn) concentrations in AD compared with other neurodegenerative diseases and healthy controls. Methods The pathophysiological role of CSF α-syn in asymptomatic subjects at risk of AD has not been explored. We performed a large-scale cross-sectional observational monocentric study of preclinical individuals at risk for AD (INSIGHT-preAD). Results We found a positive association between CSF α-syn concentrations and brain β-amyloid deposition measures as mean cortical standard uptake value ratios. We demonstrate positive correlations between CSF α-syn and both CSF t-tau and p-tau 181 concentrations. Discussion Animal models presented evidence, indicating that α-syn may synergistically and directly induce fibrillization of both tau and β-amyloid. Our data indicate an association of CSF α-syn with AD-related pathophysiological mechanisms, during the preclinical phase of the disease.

Published
2018

13. Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality

Author

Riccelli, R, Toschi, N, Nigro, S, Terracciano, A, Passamonti, L, Passamonti, Luca [0000-0002-7937-0615], and Apollo - University of Cambridge Repository

Subjects
Adult, Cerebral Cortex, Male, Neuroticism, Brain Mapping, Settore FIS/07, Statistics as Topic, Individuality, Factor V, Prefrontal Cortex, Original Articles, surface area, Organ Size, cortical thickness, cortical folding, Magnetic Resonance Imaging, Temporal Lobe, Young Adult, big five, Image Interpretation, Computer-Assisted, Humans, Female, individual differences, Personality
Abstract

The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project. Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal–temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal–parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders.

Published
2017

15. Blood-based systems biology biomarkers for next-generation clinical trials in Alzheimer’s disease

Author

Hampel, H, Vergallo, A, Afshar, M, Akman-Anderson, L, Arenas, J, Benda, N, Batrla, R, Broich, K, Caraci, F, Cuello, Ac, Emanuele, E, Haberkamp, M, Kiddle, Sj, Lucia, A, Mapstone, M, Verdooner, Sr, Woodcock, J, Lista, S, Aguilar, Lf, Babiloni, C, Baldacci, F, Black, Kl, Bokde, Alw, Bonuccelli, U, Cacciola, F, Castrillo, J, Cavedo, E, Ceravolo, R, Chiesa, Pa, Corvol, J, Cummings, Jl, Depypere, H, Dubois, B, Duggento, A, Escott-Price, V, Federoff, H, Ferretti, Mt, Fiandaca, M, Frank, Ra, Garaci, F, Geerts, H, Giorgi, Fs, Goetzl, Ej, Graziani, M, Habert, M, Herholz, K, Kapogiannis, D, Karran, E, Kim, Sh, Koronyo, Y, Koronyo-Hamaoui, M, Langevin, T, Lehericy, S, Lorenceau, J, Mango, D, Neri, C, Nistico, R, O'Bryant, Se, Palermo, G, Perry, G, Ritchie, C, Rossi, S, Saidi, A, Santarnecchi, E, Schneider, Ls, Sporns, O, Toschi, N, Villain, N, Welikovitch, La, and Younesi, E

Subjects
biomarker-drug codevelopment, Systems biology, Alzheimer's disease, systems biology, precision medicine, blood-based biomarker, context of use, pathophysiology, clinical trial, predictive biomarker, Druggability, Eligibility Determination, Disease, Computational biology, 03 medical and health sciences, 0302 clinical medicine, Drug Development, Alzheimer Disease, Humans, Medicine, Clinical Trials as Topic, business.industry, Clinical study design, Settore FIS/07, Precision medicine, Treatment efficacy, 030227 psychiatry, Clinical trial, Early Diagnosis, Alzheimer’s disease, DECIPHER, Original Article, business, Biomarkers
Abstract

Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs. .La Enfermedad de Alzheimer (EA) es una enfermedad compleja que presenta múltiples alteraciones patomecánicas, que se desencadena por interacciones dinámicas no lineales de factores de riesgo genéticos / epigenéticos y ambientales, los que, en definitiva, convergen en una enfermedad biológicamente heterogénea. Para hacer frente a la carga de la EA durante las etapas preclínicas tempranas, actualmente se están desarrollando biomarcadores sanguíneos de fácil accesibilidad. Específicamente, se espera que los ensayos clínicos de próxima generación integren biomarcadores sanguíneos predictivos tanto positivos como negativos en los diseños de los estudios para evaluar, a nivel individual, la capacidad de la droga objetivo y los posibles mecanismos de resistencia a los medicamentos. En este contexto, la biología de sistemas promete acelerar la validación y la calificación de su empleo en los ensayos clínicos, incluida la prueba del mecanismo, la selección de pacientes, la evaluación de la eficacia del tratamiento y los porcentajes de seguridad, y la evaluación pronóstica. A pesar de estar en sus comienzos, los enfoques basados en la biología de sistemas están preparados para identificar “firmas” de EA relevantes a través de la variabilidad multifactorial e interindividual, lo que nos permite descifrar la fisiopatología y la etiología de la enfermedad. Ojalá, las estrategias innovadoras conjuntas del desarrollo de biomarcadores y de medicamentos sean el camino adecuado para conseguir fármacos eficaces que modifiquen la enfermedad.La maladie d’Alzheimer (MA) — maladie complexe présentant des altérations nombreuses pathomécaniques — est déclenchée par des interactions dynamiques non linéaires entre des facteurs de risques génétiques et épigénétiques et environnementaux qui, au bout du compte, aboutissent à une maladie biologiquement hétérogène. Pour réduire la charge de morbidité de la MA durant ses premiers stades précliniques, des biomarqueurs sanguins sont actuellement développés. Spécifiquement, la prochaine génération d’essais cliniques devrait intégrer ces biomarqueurs sanguins positifs ou négatifs prédictifs de la maladie dans des études qui auront pour but d’évaluer, à un niveau individuel, des cibles pouvant être traitées par des candidats médicaments et de potentiels mécanismes de résistance à ces médicaments. Dans ce contexte, la biologie des systèmes devrait permettre d’accélérer la validation et la qualification de leur utilisation dans les études cliniques – incluant la preuve du mécanisme d’action, la sélection des patients, la confirmation de l’efficacité du traitement et son niveau de sécurité, ainsi que l’évaluation pronostique. Bien que nous en soyons au tout début, les approches reposant sur la biologie des systèmes sont sur le point d’identifier des « signatures » pertinentes de la MA grâce à des variables multifactorielles et interindividuelles, qui nous permettront d’élucider la pathophysiologie et l’étiologie de la maladie. Avec un peu de chance, les stratégies innovantes de codéveloppement de biomarqueurs et de médicaments nous mèneront vers des médicaments efficaces pour lutter contre la maladie.

Published
2019

16. Brain Aβ load association and sexual dimorphism of plasma BACE1 concentrations in cognitively normal individuals at risk for AD

Author

Vergallo, A., Houot, M., Cavedo, E., Lemercier, P., Vanmechelen, E., De Vos, A., Habert, M. -O., Potier, M. -C., Dubois, B., Lista, S., Hampel, H., Bakardjian, H., Benali, H., Bertin, H., Bonheur, J., Boukadida, L., Boukerrou, N., Chiesa, P., Colliot, O., Dubois, M., Epelbaum, S., Gagliardi, G., Genthon, R., Habert, M. O., Kas, A., Lamari, F., Levy, M., Metzinger, C., Mochel, F., Nyasse, F., Poisson, C., Potier, M. C., Revillon, M., Santos, A., Andrade, K. S., Sole, M., Surtee, M., Thiebaud de Schotten, M., Younsi, N., Afshar, M., Flores Aguilar, L., Akman-Anderson, L., Arenas, J., Avila, J., Babiloni, C., Baldacci, F., Batrla, R., Benda, N., Black, K. L., Bokde, A. L. W., Bonuccelli, U., Broich, K., Cacciola, F., Caraci, F., Castrillo, J., Ceravolo, R., Chiesa, P. A., Corvol, J. -C., Claudio Cuello, A., Cummings, J. L., Depypere, H., Duggento, A., Emanuele, E., Escott-Price, V., Federoff, H., Teresa Ferretti, M., Fiandaca, M., Frank, R. A., Garaci, F., Geerts, H., Giorgi, F. S., Goetzl, E. J., Graziani, M., Haberkamp, M., Marie-Odile, H., Herholz, K., Hernandez, F., Kapogiannis, D., Karran, E., Kiddle, S. J., Kim, S. H., Koronyo, Y., Koronyo-Hamaoui, M., Langevin, T., Lehericy, S., Lucia, A., Lorenceau, J., Mango, D., Mapstone, M., Neri, C., Nistico, R., O'Bryant, S. E., Palermo, G., Perry, G., Ritchie, C., Rossi, S., Saidi, A., Santarnecchi, E., Schneider, L. S., Sporns, O., Toschi, N., Verdooner, S. R., Villain, N., Welikovitch, L. A., Woodcock, J., Younesi, E., Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre d'investigation clinique Neurosciences [CHU Pitié Salpêtrière] (CIC Neurosciences), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Service de médecine nucléaire [CHU Pitié-Salpétrière]

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Epidemiology, [SDV]Life Sciences [q-bio], PROGRESSION, Disease, Cognition, 0302 clinical medicine, Amyloid precursor protein, Medicine and Health Sciences, Aspartic Acid Endopeptidases, medicine.diagnostic_test, biology, Health Policy, Settore BIO/14, Brain, Alzheimer's disease, Healthy Volunteers, 3. Good health, GENOTYPE, ALZHEIMERS-DISEASE, Psychiatry and Mental health, Positron emission tomography, Cohort, Biomarker (medicine), Female, EXPRESSION, medicine.medical_specialty, BIOMARKERS, Standardized uptake value, 03 medical and health sciences, Cellular and Molecular Neuroscience, Sexual dimorphism, Apolipoproteins E, Sex Factors, Developmental Neuroscience, Alzheimer Disease, Internal medicine, mental disorders, medicine, Humans, BACE1 biomarkers, Aged, Plasma BACE1, DECLINE, Amyloid beta-Peptides, business.industry, 030104 developmental biology, Endocrinology, Positron-Emission Tomography, Disease modifying, biology.protein, Neurology (clinical), Amyloid Precursor Protein Secretases, Geriatrics and Gerontology, business, Biomarkers, 030217 neurology & neurosurgery
Abstract

Introduction: Successful development of effective beta-site amyloid precursor protein cleaving enzyme 1 (BACE1)-targeted therapies for early stages of Alzheimer's disease requires biomarker-guided intervention strategies. Methods: We investigated whether key biological factors such as sex, apolipoprotein E (APOE epsilon 4) allele, and age affect longitudinal plasma BACE1 concentrations in a large monocenter cohort of individuals at risk for Alzheimer's disease. We explored the relationship between plasma BACE1 concentrations and levels of brain amyloid-beta (A beta) deposition, using positron emission tomography global standard uptake value ratios. Results: Baseline and longitudinal mean concentrations of plasma BACE1 were significantly higher in women than men. We also found a positive significant impact of plasma BACE1 on baseline A beta-positron emission tomography global standard uptake value ratios. Discussion: Our results suggest a sexual dimorphism in BACE1-related upstream mechanisms of brain A beta production and deposition. We argue that plasma BACE1 should be considered in further biomarker validation and qualification studies as well as in BACE1 clinical trials. (C) 2019 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.

Published
2019
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17. Basal Forebrain Volume, but Not Hippocampal Volume, Is a Predictor of Global Cognitive Decline in Patients With Alzheimer's Disease Treated With Cholinesterase Inhibitors

Author

Teipel, Sj, Cavedo, E, Hampel, H, Grothe, Mj, Aguilar, Lf, Babiloni, C, Baldacci, F, Benda, N, Black, Kl, Bokde, Alw, Bonuccelli, U, Broich, K, Bun, Rs, Cacciola, F, Castrillo, J, Ceravolo, R, Chiesa, Pa, Colliot, O, Coman, C, Corvol, J, Cuello, Ac, Depypere, H, Dubois, B, Duggento, A, Durrleman, S, Escott-Price, V, Federoff, H, Ferretti, Mt, Fiandaca, M, Frank, Ra, Garaci, F, Genthon, R, George, N, Giorgi, Fs, Graziani, M, Haberkamp, M, Habert, M, Herholz, K, Karran, E, Kim, Sh, Koronyo, Y, Koronyo-Hamaoui, M, Lamari, F, Langevin, T, Lehericy, S, Lista, S, Lorenceau, J, Mapstone, M, Neri, C, Nistico, R, Nyasse-Messene, F, O'Bryant, Se, Perry, G, Ritchie, C, Rojkova, K, Rossi, S, Saidi, A, Santarnecchi, E, Schneider, Ls, Sporns, O, Toschi, N, Verdooner, Sr, Vergallo, A, Villain, N, Welikovitch, La, Woodcock, J, Younesi, E, and Cummings, Jl

Subjects
Aging, hippocampus, Hippocampus, Neurodegenerative, Alzheimer's Disease, lcsh:RC346-429, cholinergic treatment, memory, 0302 clinical medicine, Medicine and Health Sciences, Psychology, Medicine, Cognitive decline, Episodic memory, basal forebrain, Original Research, Basal forebrain, Settore FIS/07, 05 social sciences, Cognition, IMPAIRMENT, Manchester Institute for Collaborative Research on Ageing, Neurology, Neurological, Cohort, DONEPEZIL, Cardiology, NUCLEUS BASALIS, ADAS-COG, MRI, CHOLINERGIC SYSTEM, medicine.medical_specialty, ResearchInstitutes_Networks_Beacons/MICRA, Clinical Sciences, COMPOSITE SCORE, ATROPHY, 050105 experimental psychology, 03 medical and health sciences, Clinical Research, Internal medicine, Behavioral and Social Science, Acquired Cognitive Impairment, Dementia, 0501 psychology and cognitive sciences, ddc:610, lcsh:Neurology. Diseases of the nervous system, business.industry, Alzheimer's Disease Neuroimaging Initiative, Neurosciences, Alzheimer Precision Medicine Initiative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), prediction, medicine.disease, NEUROIMAGING INITIATIVE ADNI, Brain Disorders, SUBSTANTIA INNOMINATA, executive function, Cholinergic treatment, Executive function, Memory, Prediction, Cholinergic, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

Background: Predicting the progression of cognitive decline in Alzheimer's disease (AD) is important for treatment selection and patient counseling. Structural MRI markers such as hippocampus or basal forebrain volumes might represent useful instruments for the prediction of cognitive decline. The primary objective was to determine the predictive value of hippocampus and basal forebrain volumes for global and domain specific cognitive decline in AD dementia during cholinergic treatment.Methods: We used MRI and cognitive data from 124 patients with the clinical diagnosis of AD dementia, derived from the ADNI-1 cohort, who were on standard of care cholinesterase inhibitor treatment during a follow-up period between 0.4 and 3.1 years. We used linear mixed effects models with cognitive function as outcome to assess the main effects as well as two-way interactions between baseline volumes and time controlling for age, sex, and total intracranial volume. This model accounts for individual variation in follow-up times.Results: Basal forebrain volume, but not hippocampus volume, was a significant predictor of rates of global cognitive decline. Larger volumes were associated with smaller rates of cognitive decline. Left hippocampus volume had a modest association with rates of episodic memory decline. Baseline performance in global cognition and memory was significantly associated with hippocampus and basal forebrain volumes; in addition, basal forebrain volume was associated with baseline performance in executive function.Conclusions: Our findings indicate that in AD dementia patients, basal forebrain volume may be a useful marker to predict subsequent cognitive decline during cholinergic treatment.

Published
2018
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18. Depressive symptoms in cerebral small vessel disease are associated with white matter microstructural damage: the VMCI-Tuscany study

Author

Pasi, M, Poggesi, A, Salvadori, E, Ciolli, L, Del Bene, A, Marini, S, Nannucci, S, Pescini, F, Valenti, R, Ginestroni, A, Toschi, N, Mascalchi, M, Inzitari, D, Pantoni, L., DICIOTTI, STEFANO, Pasi, M, Poggesi, A, Salvadori, E, Ciolli, L, Del Bene, A, Marini, S, Nannucci, S, Pescini, F, Valenti, R, Ginestroni, A, Toschi, N, Diciotti, S, Mascalchi, M, Inzitari, D, and Pantoni, L

Subjects
small vessel disease, white matter, microstructural damage
Published
2015

19. Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain

Author

Lanzafame, S, Giannelli, M, Garaci, F, Floris, R, Duggento, A, Guerrisi, M, and Toschi, N

Subjects
diffusion models, Adult, Male, diffusion kurtosis, diffusion-MRI, Settore FIS/07, Biophysics, Brain, Middle Aged, Models, Theoretical, White Matter, DKI, DTI, non-Gaussian diffusion, Radiology, Nuclear Medicine and Imaging, Young Adult, Diffusion Tensor Imaging, Nuclear Medicine and Imaging, Image Processing, Computer-Assisted, Humans, Female, Radiology, Algorithms
Abstract

An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter.The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms.DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine.Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.

Published
2016

21. Diffusion Kurtosis Imaging: prime applicazioni cliniche in ambito neuroradiologico

Author

MARRALE, Maurizio, COLLURA, Giorgio, GAGLIARDO, Cesare, Toschi, N, MIDIRI, Massimo, BRAI, Maria, Marrale, M, Collura, G, Gagliardo, C, Toschi, N, Midiri, M, and Brai, M

Subjects
DTI, neuroradiologia, MRI, DKI, DWI, Settore MED/37 - Neuroradiologia, Settore MED/36 - Diagnostica Per Immagini E Radioterapia, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Published
2014

23. Mapping the structural organization of the brain in conduct disorder : replication of findings in two independent samples

Author

Fairchild, G, Toschi, N, Sully, K, Sonuga-Barke, Ejs, Hagan, Cc, Diciotti, S, Goodyer, Im, Calder, Aj, Passamonti, L, Goodyer, Ian [0000-0001-9183-0373], Passamonti, Luca [0000-0002-7937-0615], Apollo - University of Cambridge Repository, Fairchild, Graeme, Toschi, Nicola, Sully, Kate, Sonuga-Barke, Edmund J.S., Hagan, Cindy C., Diciotti, Stefano, Goodyer, Ian M., Calder, Andrew J., and Passamonti, Luca

Subjects
Adult, Conduct Disorder, Male, structural covariance, Adolescent, EARLY-ONSET, CHILDHOOD, SURFACE-AREA, Pediatrics, Cortical thickness, Young Adult, developmental taxonomic theory, Antisocial behavior, Conduct disorder, Developmental taxonomic theory, Structural covariance, Psychiatry and Mental Health, Pediatrics, Perinatology and Child Health, Developmental and Educational Psychology, Humans, LIFE-COURSE-PERSISTENT, Age of Onset, Cortical thickne, Cerebral Cortex, conduct disorder, ABNORMALITIES, behavior, Settore FIS/07, Original Articles, ANTISOCIAL-BEHAVIOR, Perinatology and Child Health, Magnetic Resonance Imaging, antisocial, antisocial behavior, ADOLESCENCE, Juvenile Delinquency, Original Article, HUMAN CEREBRAL-CORTEX, MRI
Abstract

BackgroundNeuroimaging methods that allow researchers to investigate structural covariance between brain regions are increasingly being used to study psychiatric disorders. Structural covariance analyses are particularly well suited for studying disorders with putative neurodevelopmental origins as they appear sensitive to changes in the synchronized maturation of different brain regions. We assessed interregional correlations in cortical thickness as a measure of structural covariance, and applied this method to investigate the coordinated development of different brain regions in conduct disorder (CD). We also assessed whether structural covariance measures could differentiate between the childhood‐onset (CO‐CD) and adolescence‐onset (AO‐CD) subtypes of CD, which may differ in terms of etiology and adult outcomes.MethodsWe examined interregional correlations in cortical thickness in male youths with CO‐CD or AO‐CD relative to healthy controls (HCs) in two independent datasets. The age range in the Cambridge sample was 16–21 years (mean: 18.0), whereas the age range of the Southampton sample was 13–18 years (mean: 16.7). We used FreeSurfer to perform segmentations and applied structural covariance methods to the resulting parcellations.ResultsIn both samples, CO‐CD participants displayed a strikingly higher number of significant cross‐cortical correlations compared to HC or AO‐CD participants, whereas AO‐CD participants presented fewer significant correlations than HCs. Group differences in the strength of the interregional correlations were observed in both samples, and each set of results remained significant when controlling for IQ and comorbid attention‐deficit/hyperactivity disorder symptoms.ConclusionsThis study provides new evidence for quantitative differences in structural brain organization between the CO‐CD and AO‐CD subtypes, and supports the hypothesis that both subtypes of CD have neurodevelopmental origins.

Published
2016
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25. Sviluppo di un software per l’analisi di immagini di Diffusion Kurtosis Imaging

Author

COLLURA, Giorgio, MARRALE, Maurizio, GAGLIARDO, Cesare, MIDIRI, Massimo, BRAI, Maria, GALLO, Salvatore, Toschi, N, Collura, G, Marrale, M, Toschi, N, Gagliardo, C, Midiri, M, Brai, M, and Gallo, S

Subjects
diffusion, diffusion tensor, diffusion kurtosis, MRI, DWI, DTI, DKI, Python, Settore MED/37 - Neuroradiologia, Settore MED/36 - Diagnostica Per Immagini E Radioterapia, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Abstract

L’analisi mediante RM del tensore di diffusione (Diffusion Tensor Imaging, DTI) consente di valutare anche in vivo e con modalità non invasive il processo di diffusione delle molecole d’acqua nei tessuti biologici. La peculiare organizzazione di alcuni tessuti biologici (es: muscoli, sostanza bianca del sistema nervoso centrale e tessuti ad alta cellularità) influenza tale fenomeno rendendolo anisotropo e quindi ben valutabile con tali tecniche di studio. Nonostante i grandi vantaggi di tale tecnica, il DTI è basato su un modello molto semplificato che assume che lo spostamento per diffusione segua un profilo gaussiano il che è molto raro in un ambiente variegato come i tessuti biologici. Per caratterizzare la natura non gaussiana della diffusione dell’acqua nei tessuti è stata sviluppata negli ultimi anni la Diffusion Kurtosis Imaging (DKI) che permette di ottenere ulteriori e più accurate informazioni sulle caratteristiche ultrastrutturali tissutali. Nel presente lavoro si è posto come obiettivo lo sviluppo di un software in grado di ricostruire le mappe tipiche della DKI. In particolare, il software è stato sviluppato in linguaggio di programmazione “Python” e permette di estrarre i parametri DTI e DKI da una serie di dati acquisiti per vari valori di b e per un vario numero di direzioni di gradienti.

Published
2013

27. The burden of microstructural damage modulates cortical activation in elderly subjects with MCI and leuko-araiosis. A DTI and fMRI study

Author

Mascalchi, M, Ginestroni, A, Toschi, N, Poggesi, A, Cecchi, P, Salvadori, E, Tessa, C, Cosottini, M, De Stefano, N, Pracucci, G, Pantoni, L, Inzitari, D, Diciotti, S, VMCI Tuscany Investigators: Inzitari, D, Abbate, R, Bandinelli, M, Boddi, M, Cesari, F, Ciolli, L, Coppo, M, Del Bene, A, Giusti, B, Gori, Am, Nannucci, S, Pasi, M, Pescini, F, Valenti, R, Bonucelli, U, Chiti, A, Orlandi, G, Pagni, C, Siciliano, G, Tognoni, G, Federico, A, Dotti, Mt, Formichi, P, Gambetti, C, Giorgio, A, Rossi, F, Stromillo, L, Zicari, E, Zolo, P, Tiezzi, A, Bertini, E, Brotini, S, Guidi, L, Lombardi, M, Mugnai, S, Notarelli, A, Bracco, L, Cadelo, M, Cisbani, R, Gabbani, L, Gori, G, Lambertucci, L, Massacesi, L, Mossello, E, Paganini, M, Piccininni, M, Pinto, F, Pozzi, C, Sorbi, S, Zaccara, G, Borgogni, T, Mancuso, M, Marconi, R, Mazzoni, M, Vista, M, Meucci, G, Bellini, G, Gabrielli, L, Frittelli, C, Galli, R, Gambaccini, G, Bartolini, S, Biagini, C, Caleri, V, Vanni, P, Calvani, D, Giorgi, C, Magnolfi, S, Palumbo, P, Valente, C, Rossi, A, Tassi, R, Boschi, S, and Baldacci, Filippo

Published
2014

30. Technical note: DTI measurements of fractional anisotropy and mean diffusivity at 1.5 T: comparison of two radiofrequency head coils with different functional designs and sensitivities

Author

Giannelli, M, Belmonte, G, Toschi, N, Pesaresi, I, Ghedin, P, Claudio Traino, A, Bartolozzi, C, and Cosottini, M

Subjects
instrumentation, Adult, Male, radiofrequency radiation, Radio Waves, Image Processing, article, Brain, Equipment Design, adult, anisotropy, brain, comparative study, diffusion tensor imaging, equipment design, female, human, image processing, male, radiofrequency radiation, Adult, Anisotropy, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Young Adult, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), Computer-Assisted
Abstract

Diffusion tensor imaging (DTI) is highly sensitive to noise and improvement of radiofrequency coil technology represents a straightforward way for augmenting signal-to-noise ratio (SNR) performance in magnetic resonance imaging (MRI) scanners. The aim of this study was to characterize the dependence of DTI measurements of fractional anisotropy (FA) and mean diffusivity (MD) on the choice of head coil, comparing two head coils with different functional designs and sensitivities.Fourteen healthy subjects underwent DTI acquisitions at 1.5 T. Every subject was scanned twice, using a standard quadrature birdcage head coil (coil-A) and an eight-channel array head coil (coil-B). FA and MD maps, estimated using both the linear least squares (LLS) and nonlinear least squares (NLLS) methods, were nonlinearly normalized into a standard space. Then, volumetric regions of interest encompassing typical white and gray matter structures [splenium of the corpus callosum (SCC), internal capsule (IC), cerebral peduncles (CP), middle cerebellar peduncles (MCP), globus pallidus (GP), thalamus (TH), caudate (CA), and putamen (PU)] were analyzed. Significant differences and trends of variation in DTI measurements were assessed by the Wilcoxon test for paired samples with and without Bonferroni correction for multiple comparisons, respectively.The overall SNR of coil-B was 30% higher than that of coil-A. When comparing DTI measurements (coil-B versus coil-A), mean FA values (SCC, IC, and TH), mean MD values (IC, CP, GP, and TH), FA standard deviation (CP, MCP, GP, and CA), and MD standard deviation (IC, CP, TH, and PU) resulted decreased (significant difference, p(cor)0.05, or trend of variation, P(uncor)0.05) in several gray and white matter regions of the human brain. With the exception of CP, the results in terms of revealed significant difference or trend of variation were independent of the method (LLS and NLLS) used for estimating the diffusion tensor.In various gray and white matter structures, the eight-channel array head coil yielded more precise and accurate measurements of DTI derived indices compared to the standard quadrature birdcage head coil.

Published
2011

45. Increased hypothalamic expression of prolactin in lactation: Involvement in behavioural and neuroendocrine stress responses

Author

Torner, L, Toschi, N, Nava, G, Clapp, C, and Neumann, I

Subjects
antisense oligonucleotide, Male, prolactin, Hypothalamo-Hypophyseal System, prolactin receptor, hypothalamus hypophysis adrenal system, animal experiment, Messenger, Oligonucleotides, Wistar, emotion, Down-Regulation, corticotropin, oxytocin, prolactin receptor, animal experiment, animal tissue, anxiety, article, behavior, controlled study, corticotropin release, down regulation, female, lactation, male, maternal behavior, maze test, milk ejection, neuroendocrinology, nonhuman, oxytocin blood level, priority journal, protein expression, rat, reverse transcription polymerase chain reaction, stress, Adrenocorticotropic Hormone, Animals, Animals, Newborn, Anxiety, Behavior, Animal, Female, Gene Expression Regulation, Lactation, Maternal Behavior, Oligonucleotides, Antisense, Oxytocin, Pregnancy, Prolactin, Rats, Rats, Wistar, Receptors, Prolactin, RNA, Messenger, Stress, Up-Regulation, Settore MED/13 - Endocrinologia, stress, Adrenocorticotropic Hormone, Receptors, Antisense, Behavior, Animal, Newborn, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), RNA
Published
2002

46. Maternal defence as an emotional stressor in female rats: Correlation of neuroendocrine and behavioural parameters and involvement of brain oxytocin

Author

Neumann, I, Toschi, N, Ohl, F, Torner, L, and Krömer, S

Subjects
animal experiment, Wistar, hormone blood level, lactation, animal behavior, neuroendocrine system, Oxytocin, Stress, corticotropin, oxytocin, aggression, article, corticotropin blood level, defensive behavior, emotional stress, female, nonhuman, priority journal, rat, Adrenocorticotropic Hormone, Animals, Behavior, Animal, Brain, Corticosterone, Fear, Female, Lactation, Maternal Behavior, Neurosecretory Systems, Prolactin, Rats, Rats, Wistar, Receptors, Oxytocin, Settore MED/13 - Endocrinologia, Adrenocorticotropic Hormone, Receptors, rat, Behavior, Animal, Settore BIO/11, aggression, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Published
2001

47. Acute transcranial magnetic stimulation of frontal brain regions selectively modulates the release of vasopressin, biogenic amines and amino acids in the rat brain

Author

Keck, M, Sillaber, I, Ebner, K, Welt, T, Toschi, N, Kaehler, S, Singewald, N, Philippu, A, Elbel, G, Wotjak, C, Holsboer, F, Landgraf, R, and Engelmann, M

Subjects
Male, vasopressin, amino acid brain level, Wistar, arginine, Hippocampus, biogenic amine, 4 aminobutyric acid, Models, transcranial magnetic stimulation, rat, hypothalamus, Amino Acids, frontal cortex, homovanillic acid, article, thalamus midline nucleus, serotonin, priority journal, neuromodulation, Neurological, glutamine, Settore MED/26 - Neurologia, dopamine, glutamic acid, taurine, 5 hydroxyindoleacetic acid, 3,4 dihydroxyphenylacetic acid, amino acid derivative, aspartic acid, noradrenalin, serine, vasopressin, amino acid brain level, animal experiment, animal tissue, brain depth stimulation, brain region, dopamine brain level, human, male, nonhuman, vasopressin release, Amino Acids, Animals, Arginine Vasopressin, Biogenic Monoamines, Electric Stimulation, Electric Stimulation Therapy, Humans, Hypothalamus, Models, Neurological, Paraventricular Hypothalamic Nucleus, Rats, Rats, Wistar, Transcranial Magnetic Stimulation, Vasopressins, vasopressin release, 4 dihydroxyphenylacetic acid, Settore MED/25 - Psichiatria, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Published
2000

48. Sequence design and practical implementation of antisense oligonucleotides in neuroendocrinology

Author

Neumann, Id, Krã¶mer, Sa, Toschi, N, and Ebner, K

Subjects
Corticotropin-Releasing Hormone, Vasopressins, Messenger, review, Oxytocin, Settore MED/13 - Endocrinologia, in vivo study, Receptors, binding kinetics, Animals, nucleic acid probe, Antisense, degradation, messenger RNA, binding kinetics, methodology, neuroendocrinology, nonhuman, priority journal, supraoptic nucleus, thalamus midline nucleus, Animals, Drug Design, Neuroendocrinology, Neuropeptides, Nucleic Acid Conformation, Oligodeoxyribonucleotides, Antisense, Paraventricular Hypothalamic Nucleus, Rats, Receptors, Neuropeptide, RNA, Messenger, Supraoptic Nucleus, messenger RNA, Settore BIO/11, thalamus midline nucleus, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), Neuropeptide, Oligodeoxyribonucleotides, RNA
Published
2000

49. Increased instability of heartbeat dynamics in Parkinson's disease

Author

Barbieri, R., Citi, L., Valenza, G., Guerrisi, M., Stefano Orsolini, Tessa, C., Diciotti, S., Toschi, N., Barbieri R, Valenza G, Citi L, Guerrisi M, Orsolini S, Tessa C, Diciotti S, and Toschi N

Subjects
heartbeat dynamic, Computer Science (all), Settore FIS/07, Parkinson’s disease, Cardiology and Cardiovascular Medicine

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